Implementazione Sistemi RAG

Building Retrieval-Augmented Generation systems that enhance LLM capabilities by grounding responses in your specific knowledge bases, documents, and data sources. We implement sophisticated document processing pipelines, embedding generation, vector database management, and semantic search capabilities. Our RAG systems intelligently retrieve relevant context, rerank results, and inject information into prompts to generate accurate, verifiable responses. We optimize chunk sizes, overlap strategies, and retrieval parameters for your content types. The implementation includes source citation, freshness management, and access control. This approach dramatically improves answer accuracy while reducing hallucinations and enabling LLMs to work with your proprietary information.